Image mosaicing via quadric surface estimation with priors for tunnel inspection

In this paper, a system which constructs a mosaic image of the tunnel surface with little distortion is presented. The tunnel surface is typically composed of a roughly cylindrical surface and protuberant regions containing objects such as pipes, pans and tunnel ridges. Since the true surface is neither planar nor quadric, existing mosaicing methods, which assume either homography or quadratic motion models, suffer from distortion. The proposed system obtains a sparse 3D model of the tunnel by multi-view reconstruction. Then, the Support Vector Machine (SVM) classifier is applied in order to separate image features lying on the cylindrical surface from those of the non-surface. The reconstructed 3D points are reprojected into images to retrieve the priors given by the SVM classifier for accurate cylindrical surface estimation. The final mosaic image is obtained by flattening the estimated textured surface onto a plane. The results suggest that the mosaic quality depends critically on the surface estimation accuracy and the proposed system is able to produce the mosaic image that preserves all physical sense, e.g. line parallelism and straightness, which is important for tunnel inspection.